diff options
Diffstat (limited to 'ethosu/vela/test')
| -rw-r--r-- | ethosu/vela/test/test_supported_operators.py | 9 | ||||
| -rw-r--r-- | ethosu/vela/test/testutil.py | 24 |
2 files changed, 27 insertions, 6 deletions
diff --git a/ethosu/vela/test/test_supported_operators.py b/ethosu/vela/test/test_supported_operators.py index 20d448d7..1fb452cf 100644 --- a/ethosu/vela/test/test_supported_operators.py +++ b/ethosu/vela/test/test_supported_operators.py @@ -30,11 +30,14 @@ support = SupportedOperators() def create_strided_slice_op(in_shape, out_shape, start_offsets, end_offsets): + qp = QuantizationParameters() in0 = Tensor(in_shape, DataType.uint8, "in") - in1 = create_const_tensor("begin", [len(start_offsets)], DataType.uint8, start_offsets) - in2 = create_const_tensor("end", [len(end_offsets)], DataType.uint8, end_offsets) - in3 = create_const_tensor("strides", [len(end_offsets)], DataType.uint8, len(end_offsets) * [1]) + in0.quantization = qp + in1 = create_const_tensor("begin", [len(start_offsets)], DataType.uint8, start_offsets, quantization=qp) + in2 = create_const_tensor("end", [len(end_offsets)], DataType.uint8, end_offsets, quantization=qp) + in3 = create_const_tensor("strides", [len(end_offsets)], DataType.uint8, len(end_offsets) * [1], quantization=qp) out = Tensor(out_shape, DataType.uint8, "out") + out.quantization = qp attrs = {"ellipsis_mask": 0, "new_axis_mask": 0, "shrink_axis_mask": 0, "begin_mask": 0, "end_mask": 0} return testutil.create_op(Op.StridedSlice, [in0, in1, in2, in3], out, attrs=attrs) diff --git a/ethosu/vela/test/testutil.py b/ethosu/vela/test/testutil.py index adb874a0..c5ff0033 100644 --- a/ethosu/vela/test/testutil.py +++ b/ethosu/vela/test/testutil.py @@ -22,6 +22,7 @@ from ethosu.vela.data_type import DataType from ethosu.vela.nn_graph import Subgraph from ethosu.vela.operation import Operation from ethosu.vela.tensor import create_const_tensor +from ethosu.vela.tensor import QuantizationParameters from ethosu.vela.tensor import Tensor @@ -38,7 +39,17 @@ def create_arch(): ) -def create_elemwise_op(type, name, ifm_shape, ifm2_shape, ofm_shape, datatype=DataType.uint8): +def create_elemwise_op( + type, + name, + ifm_shape, + ifm2_shape, + ofm_shape, + datatype=DataType.uint8, + ifm_quant=QuantizationParameters(), + ifm2_quant=QuantizationParameters(), + ofm_quant=QuantizationParameters(), +): # Creates elementwise operation with constant IFM/IFM2 if datatype.size_in_bytes() == 1: np_type = np.uint8 @@ -47,9 +58,16 @@ def create_elemwise_op(type, name, ifm_shape, ifm2_shape, ofm_shape, datatype=Da else: np_type = np.int32 op = Operation(type, name) - op.add_input_tensor(create_const_tensor(name + "_ifm", ifm_shape, datatype, np.zeros(ifm_shape), np_type)) - op.add_input_tensor(create_const_tensor(name + "_ifm2", ifm2_shape, datatype, np.zeros(ifm2_shape), np_type)) + op.add_input_tensor( + create_const_tensor(name + "_ifm", ifm_shape, datatype, np.zeros(ifm_shape), np_type, quantization=ifm_quant) + ) + op.add_input_tensor( + create_const_tensor( + name + "_ifm2", ifm2_shape, datatype, np.zeros(ifm2_shape), np_type, quantization=ifm2_quant + ) + ) ofm = Tensor(ofm_shape, datatype, name + "_ofm") + ofm.quantization = ofm_quant op.set_output_tensor(ofm) return op |